Risk Factors Associated with Preventable Hospitalisation among Rural Community-Dwelling Patients: A Systematic Review
Bibliographic record
Abstract
Potentially preventable hospitalisations (PPHs) are common and increase the burden on already stretched healthcare services. Increasingly, psychosocial factors have been recognised as contributing to PPHs and these may be mitigated through greater attention to social capital. This systematic review investigates the factors associated with PPHs within rural populations. The review was designed, conducted, and reported according to PRISMA guidelines and registered with Prospero (ID: CRD42020152194). Four databases were systematically searched, and all potentially relevant papers were screened at the title/abstract level, followed by full-text review by at least two reviewers. Papers published between 2000-2022 were included. Quality assessment was conducted using Newcastle-Ottawa Scale and CASP Qualitative checklist. Of the thirteen papers included, eight were quantitative/descriptive and five were qualitative studies. All were from either Australia or the USA. Access to primary healthcare was frequently identified as a determinant of PPH. Socioeconomic, psychosocial, and geographical factors were commonly identified in the qualitative studies. This systematic review highlights the inherent attributes of rural populations that predispose them to PPHs. Equal importance should be given to supply/system factors that restrict access and patient-level factors that influence the ability and capacity of rural communities to receive appropriate primary healthcare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".